Fei-Fei Li, Professor at Stanford University & Chief Technologist at Google Cloud
Fei-Fei Li came to the U.S. from China at 16 with a love for science and she never looked back. Educated at Princeton and Caltech, her early work in robotics revolutionized machine learning and AI. Her focus on inclusion in tech careers and diversity in what we teach machines suggests that tomorrow’s robots won’t be sexist.
FEI-FEI LI: My role is to be the thought leader of AI and machine learning. One of the most important things for me is not only to advance AI, but also to democratize AI.
My childhood was spent in the southwest of China in villages at the outskirts of the city called Chengdu. So it's a very cloudy city. You don't see starry nights too often, which actually made me really long for those few nights that have clear sky. So I always had that very early sense of wonder of what nature is, who we are. Then as I entered school, just the sheer beauty of math and science just always attracted me.
The transition from China to America was quite a shocker. Typical immigrant story that you have to start from ground zero. And I pretty much learned English from scratch here. One big difference of American school is the books are so much heavier. I had to carry all these, you know, volumetric dictionaries to survive my day.
There was one thing about Princeton that was absolutely my dream is I've always been the nerdy kid. So you know, I would never be so popular because I'm not part of any sports teams. But that intense intellectual environment-- I was like a fish in the water, suddenly.
Visual intelligence is the primary sensory system for humans to use to survive, to work, to communicate. Solving the core fundamental problems of visual intelligence is solving intelligence. If we want to ever make robots do tasks for us or with us, robots need to recognize objects.
Most people were skeptical. So we had pretty scathing reviews for grants to support this project. I didn't spend too much time thinking, oh, my god, these people don't like it. Should I do it or not? Because I know in my mind this will change how we think about machine learning. It was staggering for a while. We ended up employing tens of thousands of online workers across more than 150 countries in the world to help us assemble this data set.
The field of AI, as well as the greater field of STEM, is massively lacking diversity. We need to be mindful that human values define machine values. If our training data misses a big population of our world, that would have grave consequences.
When we have a diverse group of technologists, it's more likely that the technology will reflect our collective values. How do we encourage the future generation of technologists? If we communicate the humanistic value and how it will make our world better, we can hope to encourage more diverse groups of students to feel passionate about AI, then become tomorrow's technology leaders.
MAKERS amplifies the dialogue around harassment, equal pay and other urgent issues, pushing the women's movement forward. #RAISEYOURVOICE